MEng in Computer Science
Graduation Requirements
30 Credits
2025-2026 Academic Year
Technical Courses (18 credits)
- 15 CS course credits — 3 Credits each
- 3 credits of Technical Electives (5000 and above, choose from CS, ORIE, ECE, and INFO courses)
Studio Courses (8 credits)
All Studio courses must be taken for a letter grade.
- TECH 5900 Product Studio — 4 Credits
- TECH 5910 Startup Studio, TECH 5920 BigCo Studio, or TECH 5930 PiTech Impact Studio — 3 Credits
- TECH Studio Elective — 1 Credit
Please note: TECHIE prefix classes do not qualify as Studio electives.
General Electives (4 credits)
- Select from any offerings on Cornell Tech’s campus (CS, ECE, ORIE, INFO, LAW, NBAY, TECH, TECHIE).
Additional Requirements
- Cornell Tech campus policy indicates that students enrolled in full-time masters programs are required to maintain a minimum of 12 credits of enrollment each semester. Students are advised to enroll in an average of 15 credits each semester, unless your program requirements notes otherwise, to ensure progression towards degree completion. This policy does not apply to students enrolled in Cornell Tech’s part-time programs (CS and LLM).
- Students may not enroll in more than 18 credits per semester without Program Director approval, which will be granted only in exceptional circumstances.
- Students may only count a maximum of 2 credit hours graded as S/U towards the degree requirements. Classes that are only offered as S/U count towards this 2-credit limit. If students change a course that is more than 2 credits to “S/U”, then that entire course will not count as it is over the 2-credit limit.
- All students must receive a B or higher in TECH 5900 or TECH 5910/ TECH 5920/ TECH 5930.
- Only classes with a grade of C- or higher will count towards a student’s degree requirements.
- Students must maintain at least a 2.5 GPA. Students who are not in good standing may be asked to leave the program.
- Please note Curricular Practical Training credits (TECH 5999) does not count towards graduation/degree requirements.
Additional Option
The Security, Trust, and Safety (SETS) Certificate
The Security, Trust, and Safety (SETS) certificate is an optional path within the Computer Science M.Eng. program. It collects Cornell Tech’s courses on computer and network security, data privacy, and user safety in a selection aimed at students interested in adversarial threats to technology and countermeasures. Please note: Certificates are not part of the official university degree and will not appear on your diploma or transcript. They are designed to demonstrate specialized expertise.
Requirements
Must take at least 3 out of the following 6 courses:
- CS 5342 / INFO 5320 Trust and Safety: Platforms, Policies, Products
- CS 5435 Security & Privacy Concepts in the Wild
- CS 5436 / INFO 5303 Privacy in the Digital Age
- CS 5830 Applied Cryptography
- CS 5433 Blockchains, Cryptocurrencies, and Smart Contracts
- CS XXXX Trustworthy AI
In addition, choose one of the law courses below:
- LAW 6568 Internet Law, Privacy and Security
- LAW 7710 Content Moderation and Platform Regulation (enrollment extremely limited)
- LAW 6273 Cybersecurity and Data Privacy Law & Regulation
- LAW 6146 AI Law and Policy
- LAW 6105 Crypto and Blockchain Finance, Law and Policy: Deciphering DeFi
More information will be shared out ahead of the Fall semester.
The AI for Engineers Certificate
The AI for Engineers certificate has an AI-focused selection of courses. It covers all aspects of modern artificial intelligence and machine learning, from fundamental algorithms to real-world systems and practical applications. It also includes courses on risks, ethics, laws, and the regulation of AI technology. Please note: Certificates are not part of the official university degree and will not appear on your diploma or transcript. They are designed to demonstrate specialized expertise.
Requirements
Choose at least three of the following, including at least one course marked with *. Other courses will need permission from the Program Director:
- CS 5785 Applied Machine Learning (*)
- CS 5781 Machine Learning Engineering (*)
- CS 5787 Deep Learning (*)
- Generative AI
- CS 6789 Reinforcement Learning
- CS 5740 Natural Language Processing
- CS 5670 Computer Vision
- CS XXXX Trustworthy AI
In addition, choose one of the courses below:
- LAW 6146 AI Law and Policy
- LAW 6336 Law and Regulation of Artificial Intelligence
- CS 5382 Practical Principles for Designing Fair Algorithms
- INFO 5600 AI for Healthcare
- INFO 5375 Health Tech-Oriented Machine Learning
- ORIE 5381 Optimization for AI
More information will be shared out ahead of the Fall semester.
